Introduction to HuggingFace Model Downloader
The HuggingFace Model Downloader is a specialized tool designed for the efficient downloading of models and datasets from the HuggingFace platform. It optimizes the downloading process by employing multithreaded techniques, especially for handling large files stored in Git Large File Storage (LFS). An integral feature of this tool is its ability to verify the integrity of downloaded files using SHA256 checksum verification, ensuring that users receive exactly what they expect.
Motivation
The tool was developed to address the challenges associated with the slow speed of Git LFS. The creator also aimed for a solution that could be easily integrated into projects requiring model inference, particularly those that use a combination of Go and Python programming languages.
Quick Installation
Getting started with the tool is remarkably straightforward, thanks to a one-line installer compatible with Linux, Mac, and Windows WSL2 systems. This installer detects the operating system and architecture, downloading the appropriate binary and saving it as "hfdownloader" in the current folder. For users that prefer installing the tool into the default OS binary folder, there is an option to do so by simply providing a command parameter.
bash <(curl -sSL https://g.bodaay.io/hfd) -h
For installation into the default OS bin:
bash <(curl -sSL https://g.bodaay.io/hfd) -i
Custom installation directories are also supported:
bash <(curl -sSL https://g.bodaay.io/hfd) -i -p ~/.local/bin/
Exemplary Usage
The utility of the HuggingFace Model Downloader extends to diverse use cases as demonstrated by various example commands. Downloading entire models or specific subsets of model files is made simple and efficient.
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Downloading a Specific Model:
To download a model like TheBloke/orca_mini_7B-GPTQ:
bash <(curl -sSL https://g.bodaay.io/hfd) -m TheBloke/orca_mini_7B-GPTQ -
Fetching Specific Variants:
When a specific variant of a model (such as GGML variant q4_0 of TheBloke/vicuna-13b-v1.3.0) is needed:
bash <(curl -sSL https://g.bodaay.io/hfd) -m TheBloke/vicuna-13b-v1.3.0-GGML:q4_0 -
Concurrent Connections:
The tool allows using multiple connections to expedite the download process, for instance, utilizing eight connections to save data into a specific directory (
/workspace/):bash <(curl -sSL https://g.bodaay.io/hfd) -c 8 -s /workspace/
Features and Benefits
The HuggingFace Model Downloader is brimming with features designed to enhance user experience and utility:
- Multithreaded Downloads: Rapidly download large files via multiple concurrent connections.
- File Verification: Maintain data integrity through SHA256 checksum verification.
- Integrated Filtering: Efficiently download only the necessary parts of model files, particularly useful for complex quantized models.
- Configurable Tool: A single binary that can be used as a standalone utility or integrated as a library in larger projects.
- Access Control: Support for securely downloading restricted models or datasets using a HuggingFace Access Token.
- Resume Capability: Interrupted downloads can be resumed smoothly without data loss.
- Configuration Files: Easily manage default settings with configuration files, and generate template configuration files for custom scenarios.
Conclusion
The HuggingFace Model Downloader stands as a robust tool for anyone needing seamless model and dataset downloads from HuggingFace. Its careful design addresses common Git LFS issues while providing flexibility and speed for model deployment and development needs, making it an invaluable asset in machine learning workflows.